In this installment of my “Embedded Toolbox” series, I would like to share with you the free source code cleanup utility called QClean for cleaning whitespace in your source files, header files, makefiles, linker scripts, etc.

You probably wonder why you might need such a utility? In fact, the common thinking is that compilers (C, C++, etc.) ignore whitespace anyway, so why bother? But, as a professional software developer you should not ignore whitespace, because it can cause all sorts of problems, some of them illustrated in the figure below:

Trailing whitespace after the last printable character in line can cause bugs. For example, trailing whitespace after the C/C++ macro-continuation character ‘\’ can confuse the C pre-processor and can result in a program error, as indicated by the bug icons.

Similarly, inconsistent use of End-Of-Line (EOL) convention can cause bugs. For example, mixing the DOS EOL Convention (0x0D,0x0A) with Unix EOL Convention (0x0A) can confuse the C pre-processor and can result in a program error, as indicated by the bug icons.

Varying amount of trailing whitespace at the end of the lines plus inconsistent use of tabs and spaces can cause unnecessary churn in the version control system (VCS) in source files that otherwise should be identical. Sure, many VCSs allow you to “ignore whitespace”, but are files differing in size by as much as 20% really identical?

Inconsistent use of tabs and spaces can lead to different rendering of the source code by different editors and printers.

Note: The problems caused by whitespace in the source code are particularly insidious, because you don’t see the culprit. By using an automated whitespace cleanup utility you can save yourself hours of frustration and significantly improve your code quality.

QClean Source Code Cleanup Utility

QClean is a simple and blazingly fast command-line utility to automatically clean whitespace in your source code. QClean is deployed as natively compiled executable and is located in the QTools Collection (in the sub-directory qtools/bin ). QClean is also available in portable source code and can be adapted and re-compiled on all desktop platforms (Windows, POSIX –Linux, MacOS).

Using QClean

Typically, you invoke QClean from a command-line prompt without any parameters. In that case, QClean will cleanup white space in the current directory and recursively in all its sub-directories.

Note: If you have added the qtools/bin/ directory to your PATH environment variable (see Installing QTools), you can run qclean directly from your terminal window.

As you can see in the screen shot above, QClean processes the files and prints out the names of the cleaned up files. Also, you get information as to what has been cleaned, for example, “Trail-WS” means that trailing whitespace has been cleaned up. Other possibilities are: “CR” (cleaned up DOS/Windows (CR) end-of-lines), “LF” (cleaned up Unix (LF) end-of-lines), and “Tabs” (replaced Tabs with spaces).

Long Lines

QClean can optionally check the code for long lines of code that exceed a specified limit (80 characters by default) to reduce the need to either wrap the long lines (which destroys indentation), or the need to scroll the text horizontally. (All GUI usability guidelines universally agree that horizontal scrolling of text is always a bad idea.) In practice, the source code is very often copied-and-pasted and then modified, rather than created from scratch. For this style of editing, it’s very advantageous to see simultaneously and side-by-side both the original and the modified copy. Also, differencing the code is a routinely performed action of any VCS (Version Control System) whenever you check-in or merge the code. Limiting the line length allows to use the horizontal screen real estate much more efficiently for side-by-side-oriented text windows instead of much less convenient and error-prone top-to-bottom differencing.

QClean File Types

QClean applies the following rules for cleaning the whitespace depending on the file types:

FILE TYPE

END-OF-LINE

TRAILING WS

TABS

LONG-LINES

.c

Unix (LF)

remove

remove

check

.h

Unix (LF)

remove

remove

check

.cpp

Unix (LF)

remove

remove

check

.hpp

Unix (LF)

remove

remove

check

.s

Unix (LF)

remove

remove

check

.asm

Unix (LF)

remove

remove

check

.lnt

Unix (LF)

remove

remove

check

.txt

DOS (CR,LF)

remove

remove

don’t check

.md

DOS (CR,LF)

remove

remove

don’t check

.bat

DOS (CR,LF)

remove

remove

don’t check

.ld

Unix (LF)

remove

remove

check

.tcl

Unix (LF)

remove

remove

check

.py

Unix (LF)

remove

remove

check

.java

Unix (LF)

remove

remove

check

Makefile

Unix (LF)

remove

leave

check

.mak

Unix (LF)

remove

leave

check

.html

Unix (LF)

remove

remove

don’t check

.htm

Unix (LF)

remove

remove

don’t check

.php

Unix (LF)

remove

remove

don’t check

.dox

Unix (LF)

remove

remove

don’t check

.m

Unix (LF)

remove

remove

check

The cleanup rules specified in the table above can be easily customized by editing the array l_fileTypes in the qclean/source/main.c file. Also, you can change the Tab sizeby modifying the TAB_SIZE constant (currently set to 4) as well as the default line-limit by modifying the LINE_LIMIT constant (currently set to 80) at the top of the the qclean/source/main.c file. Of course, after any such modification, you need to re-build the QClean executable and copy it into the qtools/bin directory.

Note: For best code portability, QClean enforces the consistent use of the specified End-Of-Line convention (typically Unix (LF)), regardless of the native EOL of the platform. The DOS/Windows EOL convention (CR,LF) is typically not applied because it causes compilation problems on Unix-like systems (Specifically, the C preprocessor doesn’t correctly parse the multi-line macros.) On the other hand, most DOS/Windows compilers seem to tolerate the Unix EOL convention without problems.

Summary

QClean is very simple to use (no parameters are needed in most cases) and is fast (it can easily cleanup hundreds of files per second). All this is designed so that you can use QClean frequently. In fact, the use of QClean after editing your code should become part of your basic hygiene–like washing hands after going to the bathroom.

Like any craftsman, I have accumulated quite a few tools during my embedded software development career. Some of them proved to me more useful than others. And these generally useful tools ended up in my Embedded Toolbox. In this blog, I’d like to share some of my tools with you. Today, I’d like to start with my cross-platform Programmer’s Calculator called QCalc.

I’m sure that you already have your favorite calculator online or on your smartphone. But can your calculator accept complete expressions in the C-syntax, which you can cut-and-paste directly to and from your embedded code? How many buttons do you need to push to see your result in decimal, hex and binary? Well, QCalc can do this with less hassle than anything else I’ve seen out there. I begin with describing QCalc features and then I tell you how to download and launch it.

QCalc Features

Expressions in C-Syntax

The most important feature of QCalc is that it accepts expressions in the C-syntax – with the same operands and precedence rules as in the C or C++ source code. Among others, the expressions can contain all bit-wise operators (<<, >>, |, &, ^, ~) as well as mixed decimal, hexadecimal and even binary constants. QCalc is also a powerful floating-point scientific calculator and supports all mathematical functions (sin(), cos(), tan(), exp(), ln(), …). Some examples of acceptable expressions are:

NOTE: QCalc internally uses the Tcl command expr to evaluate the expressions. Please refer to the documentation of the Tcl expr command for more details of supported syntax and features.

Automatic conversion to hexadecimal and binary

If the result of expression evaluation is integer (as opposed to floating point), QCalc automatically displays the result in hexadecimal and binary formats (see QCalc GUI). For better readability the hex display shows a comma between the two 16-bit half-words (e.g., 0xDEAD,BEEF). Similarly, the binary output shows a comma between the four 8-bit bytes (e.g., 0b11011110,10101101,10111110,11101111).

Binary constants

As the extension to the C-syntax, QCalc supports binary numbers in the range from 0-15 (0b0000-0b1111). These binary constants are represented as $0000, $0001, $0010,…, $1110, and $1111 and can be mixed into expressions. Here are a few examples of such expressions:

($0110 << 14) & 0xDEADBEEF($0010 | $1000) * 123

History of inputs

QCalc remembers the history of up to 8 most recently entered expressions. You can recall and navigate the history of previously entered expressions by pressing the Up / Down keys.

The $ans variable

QCalc stores the result of the last computation in the $ans variable (note the dollar sign $ in front of the variable name). Here are some examples of expressions with the $ans variable:

1/$ans – find the inverse of the last computationlog($ans)/log(2) – find log-base-2 of the last computation

User variables

QCalc allows you also to define any number of your own user variables. To set a variable, you simply type the expression =alpha in the user input field. This will define the variable alpha and assign it the value of the last computation ($ans). Subsequently, you can use your alpha variable in expressions by typing $alpha (note the dollar sign $ in front of the variable name). Here is example of defining and using variable $GPIO_BASE:

0xE000E000 – set some value into $ans=GPIO_BASE – define user variable GPIO_BASE and set it to $ans$GPIO_BASE + 0x400 – use the variable $GPIO_BASE in an expression

Note: The names of user variables are case-sensitive.

Error handling

Expressions that you enter into QCalc might have all kinds of errors: syntax errors, computation errors (e.g., division by zero), undefined variable errors, etc. In all these cases, QCalc responds with the Error message and the explanation of the error:

Downloading and Launching QCalc

QCalc is included in the open source QTools Collection, which you cad freely download from SourceForge or GitHub. Once you install QTools, QCalc is located in the sub-directory qtools/bin/ and consists of a single file qcalc.tcl. To launch QCalc, you need to open this file with the wish Tk interpreter.

NOTE: The wish Tk interpreter is included in the QTools Collection for Windows and is also pre-installed in most Linux distributions.

You use QCalc by typing (or pasting) an expression in the user input field and pressing the Enter key to evaluate the expression. You can conveniently edit any expression already inside the user input field, and you can recall the previous expressions by means of the Up/Down keys. You can also resize the QCalc window to see more or less of the input field.

QCalc on Windows

The wish Tk interpreter is conveniently provided in the same qtools/bin/ directory as the qcalc.tcl script. The directory contains also a shortcut qcalc, which you can copy to your desktop.

QCalc on Linux

Most Linux distributions contain the Tk interpreter, which you can use to launch QCalc. You can do this either from a terminal, by typin wish $QTOOLS/qcalc.tcl & or by creating a shortcut to wish with the command-line argument $QTOOLS/qcalc.tcl.

An RTOS (Real-Time Operating System) is the most universally accepted way of designing and implementing embedded software. It is the most sought after component of any system that outgrows the venerable “superloop”. But it is also the design strategy that implies a certain programming paradigm, which leads to particularly brittle designs that often work only by chance. I’m talking about sequential programming based on blocking.

Blocking occurs any time you wait explicitly in-line for something to happen. All RTOSes provide an assortment of blocking mechanisms, such as time-delays, semaphores, event-flags, mailboxes, message queues, and so on. Every RTOS task, structured as an endless loop, must use at least one such blocking mechanism, or else it will take all the CPU cycles. Typically, however, tasks block not in just one place in the endless loop, but in many places scattered throughout various functions called from the task routine. For example, in one part of the loop a task can block and wait for a semaphore that indicates the end of an ADC conversion. In other part of the loop, the same task might wait for an event flag indicating a button press, and so on.

This excessive blocking is insidious, because it appears to work initially, but almost always degenerates into a unmanageable mess. The problem is that while a task is blocked, the task is not doing any other work and is not responsive to other events. Such a task cannot be easily extended to handle new events, not just because the system is unresponsive, but mostly due to the fact that the whole structure of the code past the blocking call is designed to handle only the event that it was explicitly waiting for.

You might think that difficulty of adding new features (events and behaviors) to such designs is only important later, when the original software is maintained or reused for the next similar project. I disagree. Flexibility is vital from day one. Any application of nontrivial complexity is developed over time by gradually adding new events and behaviors. The inflexibility makes it exponentially harder to grow and elaborate an application, so the design quickly degenerates in the process known as architectural decay.

The mechanisms of architectural decay of RTOS-based applications are manifold, but perhaps the worst is the unnecessary proliferation of tasks. Designers, unable to add new events to unresponsive tasks are forced to create new tasks, regardless of coupling and cohesion. Often the new feature uses the same data and resources as an already existing feature (such features are called cohesive). But unresponsiveness forces you to add the new feature in a new task, which requires caution with sharing the common data. So mutexes and other such blocking mechanisms must be applied and the vicious cycle tightens. The designer ends up spending most of the time not on the feature at hand, but on managing subtle, intermittent, unintended side-effects.

For these reasons experienced software developers avoid blocking as much as possible. Instead, they use the Active Object design pattern. They structure their tasks in a particular way, as “message pumps”, with just one blocking call at the top of the task loop, which waits generically for all events that can flow to this particular task. Then, after this blocking call the code checks which event actually arrived, and based on the type of the event the appropriate event handler is called. The pivotal point is that these event handlers are not allowed to block, but must quickly return to the “message pump”. This is, of course, the event-driven paradigm applied on top of a traditional RTOS.

While you can implement Active Objects manually on top of a conventional RTOS, an even better way is to implement this pattern as a software framework, because a framework is the best known method to capture and reuse a software architecture. In fact, you can already see how such a framework already starts to emerge, because the “message pump” structure is identical for all tasks, so it can become part of the framework rather than being repeated in every application.

This also illustrates the most important characteristics of a framework called inversion of control. When you use an RTOS, you write the main body of each task and you call the code from the RTOS, such as delay(). In contrast, when you use a framework, you reuse the architecture, such as the “message pump” here, and write the code that it calls. The inversion of control is very characteristic to all event-driven systems. It is the main reason for the architectural-reuse and enforcement of the best practices, as opposed to re-inventing them for each project at hand.

But there is more, much more to the Active Object framework. For example, a framework like this can also provide support for state machines (or better yet, hierarchical state machines), with which to implement the internal behavior of active objects. In fact, this is exactly how you are supposed to model the behavior in the UML (Unified Modeling Language).

As it turns out, active objects provide the sufficiently high-level of abstraction and the right level of abstraction to effectively apply modeling. This is in contrast to a traditional RTOS, which does not provide the right abstractions. You will not find threads, semaphores, or time delays in the standard UML. But you will find active objects, events, and hierarchical state machines.

An AO framework and a modeling tool beautifully complement each other. The framework benefits from a modeling tool to take full advantage of the very expressive graphical notation of state machines, which are the most constructive part of the UML.

In summary, RTOS and superloop aren’t the only game in town. Actor frameworks, such as Akka, are becoming all the rage in enterprise computing, but active object frameworks are an even better fit for deeply embedded programming. After working with such frameworks for over 15 years , I believe that they represent a similar quantum leap of improvement over the RTOS, as the RTOS represents with respect to the “superloop”.

Also, I recently ran into another good presentation about the same ideas. This time a NASA JPL veteran describes the best practices of “Managing Concurrency in Complex Embedded Systems”. I would say, this is exactly active object model. So, it seems that it really is true that experts independently arrive at the same conclusions…

Counting leading zeros in an integer number is a critical operation in many DSP algorithms, such as normalization of samples in sound or video processing, as well as in real-time schedulers to quickly find the highest-priority task ready-to-run.

In most such algorithms, it is important that the count-leading zeros operation be fast and deterministic. For this reason, many modern processors provide the CLZ (count-leading zeros) instruction, sometimes also called LZCNT, BSF (bit scan forward), FF1L (find first one-bit from left) or FBCL (find bit change from left).

Of course, if your processor supports CLZ or equivalent in hardware, you definitely should take advantage of it. In C you can often use a built-in function provided by the embedded compiler. A couple of examples below illustrate the calls for various CPUs and compilers:

However, what if your CPU does not provide the CLZ instruction? For example, ARM Cortex-M0 and M0+ cores do not support it. In this case, you need to implement CLZ() in software (typically an inline function or as a macro).

The Internet offers a lot of various algorithms for counting leading zeros and the closely related binary logarithm (log-base-2(x) = 32 – 1 – clz(x)). Here is a sample list of the most popular search results:

But, unfortunately, most of the published algorithms are either incomplete, sub-optimal, or both. So, I thought it could be useful to post here a complete and, as I believe, optimal CLZ(x) function, which is both deterministic and outperforms most of the published implementations, including all of the “Hacker’s Delight” algorithms.

This algorithm uses a hybrid approach of bi-section to find out which 8-bit chunk of the 32-bit number contains the first 1-bit, which is followed by a lookup table clz_lkup[] to find the first 1-bit within the byte.

The CLZ1() function is deterministic in that it completes always in 13 instructions, when compiled with IAR EWARM compiler for ARM Cortex-M0 core with the highest level of optimization.

If the ROM footprint is too high for your application, at the cost of running the bi-section for one more step, you can reduce the size of the lookup table to only 16 bytes. Here is the CLZ2() function that illustrates this tradeoff:

In the latest Lesson #10 of my Embedded C Programming with ARM Cortex-M Video Course I explain what stack overflow is and I show what can transpire deep inside an embedded microcontroller when the stack pointer register (SP) goes out of bounds. You can watch the YouTube video to see the details, but basically when the stack overflows, memory beyond the stack bound gets corrupted and your code will eventually fail. If you are lucky, your program will crash quickly. If you are less lucky, however, your program will limp along in some crippled state, not quite dead but not fully functional either. Code like this can kill people.

Unless you’ve been living under a rock for a past couple of years, you must have heard of the Toyota unintended acceleration (UA) cases, where Camry and other Toyota vehicles accelerated unexpectedly and some of them managed to kill people and all of them scared the hell out of their drivers.

The recent trial testimony delivered at the Oklahoma trial by an embedded guruMichael Barr for the fist time in history of these trials offers a glimpse into the Toyota throttle control software. In his deposition, Michael explains how a stack overflow could corrupt the critical variables of the operating system (OSEK in this case), because they were located in memory adjacent to the top of the stack. The following two slides from Michael’s testimony explain the memory layout around the stack and why stack overflow was likely in the Toyota code (see the complete set of Michael’s slides).

Barr's Slides explaining Toyota stack overflow (NOTE: the stack grows "up" in this picture, because "Top" represents a lower address in RAM than "Bottom". Traditionally, however, such a stack is called "descending".)

Why Were People Killed?

The crucial aspect in the failure scenario described by Michael is that the stack overflow did not cause an immediate system failure. In fact, an immediate system failure followed by a reset would have saved lives, because Michael explains that even at 60 Mph, a complete CPU reset would have occurred within just 11 feet of vehicle’s travel.

Instead, the problem was exactly that the system kept running after the stack overflow. But due to the memory corruption some tasks got “killed” (or “forgotten”) by the OSEK real-time operating system while other tasks were still running. This, in turn, caused the engine to run, but with the throttle “stuck” in the wide-open position, because the “kitchen-sink” TaskX, as Michael calls it, which controlled the throttle among many other things, was dead.

A Shot in the Foot

The data corruption caused by the stack overflow is completely self inflicted. I mean, we know exactly which way the stack grows on any given CPU architecture. For example, on the V850 CPU used in the Toyota engine control module (ECM) the stack grows towards the lower memory addresses, which is traditionally called a “descending stack” or a stack growing “down”. In this sense the stack is like a loaded gun that points either up or down in the RAM address space. Placing your foot (or your critical data for that matter) exactly at the muzzle of this gun doesn’t sound very smart, does it? In fact, doing so goes squarely against the very first NRA Gun Safety Rule: “ ALWAYS keep the gun pointed in a safe direction”.

A standard memory map, in which the stack grows towards your program data.

Yet, as illustrated in the Figure above, most traditional, beaten path memory layouts allocate the stack space above the data sections in RAM, even though the stack grows “down” (towards the lower memory addresses) in most embedded processors (see Table below ). This arrangement puts your program data in the path of destruction of a stack overflow. In other words, you violate the first NRA Gun Safety Rule and you end up shooting yourself in the foot, as did Toyota.

Processor Architecture

Stack growth direction

ARM Cortex-M

down

AVR

down

AVR32

down

ColdFire

down

HC12

down

MSP430

down

PIC18

up

PIC24/dsPIC

up

PIC32 (MIPS)

down

PowerPC

down

RL78

down

RX100/600

down

SH

down

V850

down

x86

down

A Smarter Way

At this point, I hope it makes sense to suggest that you consider pointing the stack in a safe direction. For a CPU with the stack growing “down” this means that you should place the stack at the start of RAM, below all the data sections. As illustrated in the Figure below, that way you will make sure that a stack overflow can’t corrupt anything.

A safer memory map, where a stack overflow can't corrupt the data.

Of course, a simple reordering of sections in RAM does nothing to actually prevent a stack overflow, in the same way as pointing a gun to the ground does not prevent the gun from firing. Stack overflow prevention is an entirely different issue that requires a careful software design and a thorough stack usage analysis to size the stack adequately.

But the reordering of sections in RAM helps in two ways. First, you play safe by protecting the data from corruption by the stack. Second, on many systems you also get an instantaneous and free stack overflow detection in form of a hardware exception triggered in the CPU. For example, on ARM Cortex-M an attempt to read to or write from an address below the beginning of RAM causes the Hard Fault exception. Later in the article I will show how to design the exception handler to avoid shooting yourself in the foot again. But before I do this, let me first explain how to change the order of sections in RAM.

How to Change the Default Order of Sections in RAM

To change the order of sections in RAM (or ROM), you typically need to edit the linker script file. For example, in a linker script for the GNU toolchain (typically a file with the .ld extension), you just move the .stack section before the .data section. The following listing shows the order of sections in the GNU .ld file (I provide the complete GNU linker script files for the Tiva-C ARM Cortex-M4F microcontroller in the code downloads accompanying my earlier article):

On the other hand, a linker script for the IAR toolchain (typically a file with the .icf extension) requires a different strategy. For some reason simple reordering of sections does not do the trick and you need to replace the last line of the standard linker script:

place in RAM_region { readwrite, block CSTACK, block HEAP };

with the following two lines:

place at start of RAM_region {block CSTACK }; /* stack at the start of RAM */
place in RAM_region { readwrite, block HEAP };

Designing an Exception Handler for Stack Overflow

As I mentioned earlier, an overflow of a descending stack placed at the start of RAM causes the Hard Fault exception on an ARM Cortex-M microcontroller. This is exactly what you want, because the exception handler provides you the last line of defense to perform damage control. However, you must be very careful how you write the exception handler, because your stack pointer (SP) is out of bounds at this point and any attempt to use the stack will fail and cause another Hard Fault exception. I hope you can see how this would lead to an endless cycle that would lock up the machine even before you had a chance to do any damage control. In other words, you must be careful here not to shoot yourself in the foot again.

So, you clearly can’t write the Hard Fault exception handler in standard C, because a standard C function most likely will access the stack. But, it is still possible to use non-standard extensions to C to get the job done. For example, the GNU compiler provides the __attribute__((naked)) extension, which indicates to the compiler that the specified function does not need prologue/epilogue sequences. Specifically, the GNU compiler will not save or restore any registers on the stack for a “naked” function. The following listing shows the definition of the HardFault_Handler() exception handler, whereas the name conforms to the Cortex Microcontroller Software Interface Standard (CMSIS):

Please note how the __attribute__((naked)) extension is applied to the declaration of the HardFault_Handler() function. The function definition is written entirely in assembly. It starts with moving the SP register into R0 and tests whether it is in bound. A one-sided check against __stack_start__ is sufficient, because you know that the stack grows “down” in this case. If a stack overflow is detected, the SP is restored back to the original end of the stack section __stack_end__. At this point the stack pointer is repaired and you can call a standard C function. Here, I call the function assert_failed(), commonly used to handle failing assertions. assert_failed() can be a standard C function, but it should not return. Its job is to perform application-specific fail-safe shutdown and logging of the error followed typically by a system reset. The code downloads accompanying this article[6] provide an example of assert_failed() implementation in the board support package (BSP).

On a side note, I’d like to warn you against coding any exception handler as an endless loop, which is another beaten path approach taken in most startup code examples provided by microcontroller vendors. Such code locks up the machine, which might be useful during debugging, but is almost never what you want in the production code. Unfortunately, all too often I see developers shooting themselves in the foot yet again by leaving this dangerous code in the final product.

For completeness, I want to mention how to implement HardFault_Handler() exception handler in the IAR toolset. The non-standard extended keyword you can use here is __stackless, which means exactly that the IAR compiler should not use the stack in the designated function. The IAR version can also use the IAR intrinsic functions __get_SP() and __set_SP() to get and set the stack pointer, respectively, instead of inline assembly:

What About an RTOS?

The technique of placing the stack at the start of RAM is not going to work if you use an RTOS kernel that requires a separate stack for every task. In this case, you simply cannot align all these multiple stacks at the single address in RAM. But even for multiple stacks, I would recommend taking a minute to think about the safest placement of the stacks in RAM as opposed to allocating the stacks statically inside the code and leaving it completely up to the linker to place the stacks somewhere in the .bss section.

Finally, I would like to point out that preemptive multitasking is also possible with a single-stack kernel, for which the simple technique of aligning the stack at the start of RAM works very well. Contrary to many misconceptions, single-stack preemptive kernels are quite popular. For example, the so called basic tasks of the OSEK-VDX standard all nest on a single stack, and therefore Toyota had to deal with only one stack (see Barr’s slides at the beginning). For more information about single-stack preemptive kernels, please refer to my article “Build a Super-Simple Tasker”.

Test it!

The most important strategy to deal with rare, but catastrophic faults, such as stack overflow is that you need to carefully design and actually test your system’s response to such faults. However, typically you cannot just wait for a rare fault to happen by itself. Instead, you need to use a technique called scientifically fault injection, which simply means that you need to intentionally cause the fault (you need to fire the gun!). In case of stack overflow you have several options: you might intentionally reduce the size of the stack section so that it is too small. You can also use the debugger to change the SP register manually. From there, I recommend that you single -step through the code in the debugger and verify that the system behaves as you intended. Chances are that you might be shooting yourself in the foot, just as it happened to Toyota.

I would be very interested to hear what you find out. Is your stack placed above the data section? Are your exception handlers coded as endless loops? Please leave a comment!